Finite element modeling of electric field effects of TASER devices on nerve and muscle

Dorin Panescu*, Mark W. Kroll, Igor R. Efimov, James D. Sweeney

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations

Abstract

Introduction: TASERs deliver electrical pulses that can temporarily incapacitate subjects. The goal of this paper is to analyze the distribution of currents in muscle layers and understand the electro-muscular incapacitation safety and efficacy of TASERs. Methods and Results: The analyses describe skeletal muscle and motor nerve activation, cell electroporation and current and electric field distributions through skin, fat and muscle layers, under worst-case assumptions for TASER electrode penetration and separation. For the muscle layer, the analysis predicts worst-case current-density and field-strength values of 94 mA/cm2 and 47 V/cm. Both values are higher than thresholds required for neuromuscular activation but significantly lower than levels needed for permanent cellular electroporation or tissue damage. Conclusion: The results indicate that TASERs are safe and effective in producing temporary subject incapacitation.

Original languageEnglish (US)
Title of host publication28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Pages1277-1279
Number of pages3
DOIs
StatePublished - 2006
Event28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 - New York, NY, United States
Duration: Aug 30 2006Sep 3 2006

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
ISSN (Print)0589-1019

Other

Other28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Country/TerritoryUnited States
CityNew York, NY
Period8/30/069/3/06

Keywords

  • Activation
  • Modeling
  • Muscle
  • Nerve
  • TASER

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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